The role of underspecification in relative clause attachment: Speed-accuracy tradeoff evidence.

A number of studies have found evidence for the so-called ambiguity advantage, that is, faster processing of ambiguous sentences compared with unambiguous counterparts. While a number of proposals regarding the mechanism underlying this phenomenon have been made, the empirical evidence so far is far from unequivocal. It is compatible with several theories, including strategic underspecification (Swets et al., 2008), race models (Logacev & Vasishth, 2016; Van Gompel et al., 2000), and a more recent coactivation-based account (Dillon et al., 2019). While all three classes of theories make matching predictions for the average time to complete relative clause (RC) attachment in ambiguous compared with unambiguous sentences, their predictions diverge with regard to the minimum completion times. The speed-accuracy tradeoff procedure was used to test the predictions of all three classes of theories. According to a hierarchical Bayesian model, the speed-accuracy tradeoff functions (SATFs) for ambiguous RC attachment conditions show an earlier departure from chance performance than in either high or low attachment conditions. The results further indicate increased asymptotic accuracy in the ambiguous condition but no increase in processing rate. Taken together, this pattern of results is compatible with the strategic underspecification model and coactivation-based accounts, but not with race models. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

When High-Capacity Readers Slow Down and Low-Capacity Readers Speed Up: Working Memory and Locality Effects.

We examined the effects of argument-head distance in SVO and SOV languages (Spanish and German), while taking into account readers' working memory capacity and controlling for expectation (Levy, 2008) and other factors. We predicted only locality effects, that is, a slowdown produced by increased dependency distance (Gibson, 2000; Lewis and Vasishth, 2005). Furthermore, we expected stronger locality effects for readers with low working memory capacity. Contrary to our predictions, low-capacity readers showed faster reading with increased distance, while high-capacity readers showed locality effects. We suggest that while the locality effects are compatible with memory-based explanations, the speedup of low-capacity readers can be explained by an increased probability of retrieval failure. We present a computational model based on ACT-R built under the previous assumptions, which is able to give a qualitative account for the present data and can be tested in future research. Our results suggest that in some cases, interpreting longer RTs as indexing increased processing difficulty and shorter RTs as facilitation may be too simplistic: The same increase in processing difficulty may lead to slowdowns in high-capacity readers and speedups in low-capacity ones. Ignoring individual level capacity differences when investigating locality effects may lead to misleading conclusions.

Understanding underspecification: A comparison of two computational implementations.

Swets et al. (2008. Underspecification of syntactic ambiguities: Evidence from self-paced reading. Memory and Cognition, 36(1), 201-216) presented evidence that the so-called ambiguity advantage [Traxler et al. (1998). Adjunct attachment is not a form of lexical ambiguity resolution. Journal of Memory and Language, 39(4), 558-592], which has been explained in terms of the Unrestricted Race Model, can equally well be explained by assuming underspecification in ambiguous conditions driven by task-demands. Specifically, if comprehension questions require that ambiguities be resolved, the parser tends to make an attachment: when questions are about superficial aspects of the target sentence, readers tend to pursue an underspecification strategy. It is reasonable to assume that individual differences in strategy will play a significant role in the application of such strategies, so that studying average behaviour may not be informative. In order to study the predictions of the good-enough processing theory, we implemented two versions of underspecification: the partial specification model (PSM), which is an implementation of the Swets et al. proposal, and a more parsimonious version, the non-specification model (NSM). We evaluate the relative fit of these two kinds of underspecification to Swets et al.'s data; as a baseline, we also fitted three models that assume no underspecification. We find that a model without underspecification provides a somewhat better fit than both underspecification models, while the NSM model provides a better fit than the PSM. We interpret the results as lack of unambiguous evidence in favour of underspecification; however, given that there is considerable existing evidence for good-enough processing in the literature, it is reasonable to assume that some underspecification might occur. Under this assumption, the results can be interpreted as tentative evidence for NSM over PSM. More generally, our work provides a method for choosing between models of real-time processes in sentence comprehension that make qualitative predictions about the relationship between several dependent variables. We believe that sentence processing research will greatly benefit from a wider use of such methods.

A Multiple-Channel Model of Task-Dependent Ambiguity Resolution in Sentence Comprehension.

Traxler, Pickering, and Clifton (1998) found that ambiguous sentences are read faster than their unambiguous counterparts. This so-called ambiguity advantage has presented a major challenge to classical theories of human sentence comprehension (parsing) because its most prominent explanation, in the form of the unrestricted race model (URM), assumes that parsing is non-deterministic. Recently, Swets, Desmet, Clifton, and Ferreira (2008) have challenged the URM. They argue that readers strategically underspecify the representation of ambiguous sentences to save time, unless disambiguation is required by task demands. When disambiguation is required, however, readers assign sentences full structure--and Swets et al. provide experimental evidence to this end. On the basis of their findings, they argue against the URM and in favor of a model of task-dependent sentence comprehension. We show through simulations that the Swets et al. data do not constitute evidence for task-dependent parsing because they can be explained by the URM. However, we provide decisive evidence from a German self-paced reading study consistent with Swets et al.'s general claim about task-dependent parsing. Specifically, we show that under certain conditions, ambiguous sentences can be read more slowly than their unambiguous counterparts, suggesting that the parser may create several parses, when required. Finally, we present the first quantitative model of task-driven disambiguation that subsumes the URM, and we show that it can explain both Swets et al.'s results and our findings.